The number of mobile computing devices in use has increased dramatically over the last decade and continues to increase. Examples of mobile computing devices are mobile telephones, digital cameras, and global positioning system (“GPS”) receivers. According to one study, 60% of the world's population has access to mobile telephones. An increasing number of people use digital cameras and some manufacturers of digital cameras presently have revenues of tens of billions of United States dollars annually. GPS receivers can be employed to identify location; measure speed, or acceleration; and for other purposes. In many cases, all three technologies are featured together in some products. As examples, there are now highly portable digital cameras embedded in mobile telephones and other handheld computing devices. Some mobile phones also have GPS receivers to enable users to find their location, directions to a destination, etc. Some digital cameras have GPS receivers to record where a photo was taken.
Digital cameras are used to capture, store, and share images. Often, the images can be viewed nearly immediately after they are captured, such as on a display device associated with the digital cameras. Once an image is captured, it can be processed by computing devices. Image recognition is one such process that can be used to recognize and identify objects in an image. For example, image recognition techniques can determine whether an image contains a human face, a particular shape, etc. Some digital cameras employ image recognition techniques to identify human faces in an image to determine focus and exposure settings. As an example, when a camera detects that the image contains a face, it may attempt to focus the camera's lens on the face and, depending on the available light, determine whether to employ a flash, and what shutter speed and lens aperture to use to capture a pleasing image. When the camera detects that the image contains two or more faces, it may attempt to select a focus point and aperture combination such that there is sufficient depth of field to capture a sharp image of all of the detected faces. Image recognition can become increasingly complex as the set of recognizable objects increases. For example, when the computing device (e.g., camera) must also identify buildings, structures, or any object or location in the world, the camera may have insufficient resources (e.g., memory and computing power) to do so.